Inference and Representation

Inference and Representation

Author: Mauricio Suarez

Publisher: University of Chicago Press

Published: 2024

Total Pages: 329

ISBN-13: 0226830047

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"Mauricio Suárez develops a conception of representation that delivers a compelling account of modeling practice. He begins by discussing the history and methodology of model building, helpfully charting the emergence of what he calls the modeling attitude, a nineteenth century and fin de siècle development. Throughout the book, prominent cases of models, both historical and contemporary, are used as benchmarks for the accounts of representation considered throughout the book. After arguing against reductive naturalist theories of scientific representation, Suárez sets out his own account: a case for pluralism regarding the means of representation and minimalism regarding its constituents. He shows that scientists employ a plurality of different modeling relations in their representational practice - which also help them to assess the accuracy of their representations - while demonstrating that there is nothing metaphysically deep about the constituent relation that encompasses all these diverse means. The book also probes the broad implications of Suárez's inferential conception outside scientific modeling itself, covering analogies with debates about artistic representation over the past several decades, as well as the consequences for epistemology of adopting an inferential conception of representation. His inferential conception is neutral between realism and instrumentalism, and he illustrates this by looking at, and briefly taking issue with, the epistemology of some of the most widely discussed philosophers in the literature"--


Book Synopsis Inference and Representation by : Mauricio Suarez

Download or read book Inference and Representation written by Mauricio Suarez and published by University of Chicago Press. This book was released on 2024 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mauricio Suárez develops a conception of representation that delivers a compelling account of modeling practice. He begins by discussing the history and methodology of model building, helpfully charting the emergence of what he calls the modeling attitude, a nineteenth century and fin de siècle development. Throughout the book, prominent cases of models, both historical and contemporary, are used as benchmarks for the accounts of representation considered throughout the book. After arguing against reductive naturalist theories of scientific representation, Suárez sets out his own account: a case for pluralism regarding the means of representation and minimalism regarding its constituents. He shows that scientists employ a plurality of different modeling relations in their representational practice - which also help them to assess the accuracy of their representations - while demonstrating that there is nothing metaphysically deep about the constituent relation that encompasses all these diverse means. The book also probes the broad implications of Suárez's inferential conception outside scientific modeling itself, covering analogies with debates about artistic representation over the past several decades, as well as the consequences for epistemology of adopting an inferential conception of representation. His inferential conception is neutral between realism and instrumentalism, and he illustrates this by looking at, and briefly taking issue with, the epistemology of some of the most widely discussed philosophers in the literature"--

Inference and Representation

Inference and Representation

Author: Mauricio Suárez

Publisher: University of Chicago Press

Published: 2024-01-11

Total Pages: 329

ISBN-13: 0226830039

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The first comprehensive defense of an inferential conception of scientific representation with applications to art and epistemology. Mauricio Suárez develops a conception of representation that delivers a compelling account of modeling practice. He begins by discussing the history and methodology of model building, charting the emergence of what he calls the modeling attitude, a nineteenth-century and fin de siècle development. Prominent cases of models, both historical and contemporary, are used as benchmarks for the accounts of representation considered throughout the book. After arguing against reductive naturalist theories of scientific representation, Suárez sets out his own account: a case for pluralism regarding the means of representation and minimalism regarding its constituents. He shows that scientists employ a variety of modeling relations in their representational practice—which helps them to assess the accuracy of their representations—while demonstrating that there is nothing metaphysically deep about the constituent relation that encompasses all these diverse means. The book also probes the broad implications of Suárez’s inferential conception outside scientific modeling itself, covering analogies with debates about artistic representation and philosophical thought over the past several decades.


Book Synopsis Inference and Representation by : Mauricio Suárez

Download or read book Inference and Representation written by Mauricio Suárez and published by University of Chicago Press. This book was released on 2024-01-11 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive defense of an inferential conception of scientific representation with applications to art and epistemology. Mauricio Suárez develops a conception of representation that delivers a compelling account of modeling practice. He begins by discussing the history and methodology of model building, charting the emergence of what he calls the modeling attitude, a nineteenth-century and fin de siècle development. Prominent cases of models, both historical and contemporary, are used as benchmarks for the accounts of representation considered throughout the book. After arguing against reductive naturalist theories of scientific representation, Suárez sets out his own account: a case for pluralism regarding the means of representation and minimalism regarding its constituents. He shows that scientists employ a variety of modeling relations in their representational practice—which helps them to assess the accuracy of their representations—while demonstrating that there is nothing metaphysically deep about the constituent relation that encompasses all these diverse means. The book also probes the broad implications of Suárez’s inferential conception outside scientific modeling itself, covering analogies with debates about artistic representation and philosophical thought over the past several decades.

Representation and Inference for Natural Language

Representation and Inference for Natural Language

Author: Patrick Blackburn

Publisher: Center for the Study of Language and Information Publica Tion

Published: 2005

Total Pages: 0

ISBN-13: 9781575864969

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How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.


Book Synopsis Representation and Inference for Natural Language by : Patrick Blackburn

Download or read book Representation and Inference for Natural Language written by Patrick Blackburn and published by Center for the Study of Language and Information Publica Tion. This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can computers distinguish the coherent from the unintelligible, recognize new information in a sentence, or draw inferences from a natural language passage? Computational semantics is an exciting new field that seeks answers to these questions, and this volume is the first textbook wholly devoted to this growing subdiscipline. The book explains the underlying theoretical issues and fundamental techniques for computing semantic representations for fragments of natural language. This volume will be an essential text for computer scientists, linguists, and anyone interested in the development of computational semantics.

Diagrammatic Representation and Inference

Diagrammatic Representation and Inference

Author: Amrita Basu

Publisher: Springer Nature

Published: 2021-09-21

Total Pages: 570

ISBN-13: 3030860620

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This book constitutes the refereed proceedings of the 12th International Conference on the Theory and Application of Diagrams, Diagrams 2021, held virtually in September 2021. The 16 full papers and 25 short papers presented together with 16 posters were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: design of concrete diagrams; theory of diagrams; diagrams and mathematics; diagrams and logic; new representation systems; analysis of diagrams; diagrams and computation; cognitive analysis; diagrams as structural tools; formal diagrams; and understanding thought processes. 10 chapters are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.


Book Synopsis Diagrammatic Representation and Inference by : Amrita Basu

Download or read book Diagrammatic Representation and Inference written by Amrita Basu and published by Springer Nature. This book was released on 2021-09-21 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 12th International Conference on the Theory and Application of Diagrams, Diagrams 2021, held virtually in September 2021. The 16 full papers and 25 short papers presented together with 16 posters were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: design of concrete diagrams; theory of diagrams; diagrams and mathematics; diagrams and logic; new representation systems; analysis of diagrams; diagrams and computation; cognitive analysis; diagrams as structural tools; formal diagrams; and understanding thought processes. 10 chapters are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Diagrammatic Representation and Inference

Diagrammatic Representation and Inference

Author: Alan Blackwell

Publisher: Springer Science & Business Media

Published: 2004-03-12

Total Pages: 469

ISBN-13: 354021268X

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This book constitutes the refereed proceedings of the Third International Conference, Diagrams 2004, held in Cambridge, UK, in March 2004. The 18 revised full papers and 42 revised poster papers presented together with a survey article and the abstracts of 2 posters were carefully reviewed and selected from a total of 91 submissions. The papers are organized in topical sections on fundamental issues, logical aspects of diagrammatic representation and reasoning, computational aspects of diagrammatic representation and reasoning, cognitive aspects of diagrammatic representation and reasoning, visualizing information with diagrams, diagrams in human-computer interaction, and diagrams in software engineering.


Book Synopsis Diagrammatic Representation and Inference by : Alan Blackwell

Download or read book Diagrammatic Representation and Inference written by Alan Blackwell and published by Springer Science & Business Media. This book was released on 2004-03-12 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference, Diagrams 2004, held in Cambridge, UK, in March 2004. The 18 revised full papers and 42 revised poster papers presented together with a survey article and the abstracts of 2 posters were carefully reviewed and selected from a total of 91 submissions. The papers are organized in topical sections on fundamental issues, logical aspects of diagrammatic representation and reasoning, computational aspects of diagrammatic representation and reasoning, cognitive aspects of diagrammatic representation and reasoning, visualizing information with diagrams, diagrams in human-computer interaction, and diagrams in software engineering.

Pattern Theory

Pattern Theory

Author: Ulf Grenander

Publisher: Oxford University Press

Published: 2007

Total Pages: 633

ISBN-13: 0198505701

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'Pattern Theory' provides a comprehensice & accessible overview of the modern challenges in signal, data & pattern analysis in speech recognition, computational linguistics, image analysis & computer vision. Aimed at graduate students the text includes numerous exercises & an extensive bibliography.


Book Synopsis Pattern Theory by : Ulf Grenander

Download or read book Pattern Theory written by Ulf Grenander and published by Oxford University Press. This book was released on 2007 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: 'Pattern Theory' provides a comprehensice & accessible overview of the modern challenges in signal, data & pattern analysis in speech recognition, computational linguistics, image analysis & computer vision. Aimed at graduate students the text includes numerous exercises & an extensive bibliography.

Diagrammatic Representation and Inference

Diagrammatic Representation and Inference

Author: Ahti-Veikko Pietarinen

Publisher: Springer Nature

Published: 2020-08-17

Total Pages: 557

ISBN-13: 3030542491

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This book constitutes the refereed proceedings of the 11th International Conference on the Theory and Application of Diagrams, Diagrams 2020, held in Tallinn, Estonia, in August 2020.* The 20 full papers and 16 short papers presented together with 18 posters were carefully reviewed and selected from 82 submissions. The papers are organized in the following topical sections: diagrams in mathematics; diagram design, principles, and classification; reasoning with diagrams; Euler and Venn diagrams; empirical studies and cognition; logic and diagrams; and posters. *The conference was held virtually due to the COVID-19 pandemic. The chapters ‘Modality and Uncertainty in Data Visualization: A Corpus Approach to the Use of Connecting Lines,’ ‘On Effects of Changing Multi-Attribute Table Design on Decision Making: An Eye Tracking Study,’ ‘Truth Graph: A Novel Method for Minimizing Boolean Algebra Expressions by Using Graphs,’ ‘The DNA Framework of Visualization’ and ‘Visualizing Curricula’ are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.


Book Synopsis Diagrammatic Representation and Inference by : Ahti-Veikko Pietarinen

Download or read book Diagrammatic Representation and Inference written by Ahti-Veikko Pietarinen and published by Springer Nature. This book was released on 2020-08-17 with total page 557 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th International Conference on the Theory and Application of Diagrams, Diagrams 2020, held in Tallinn, Estonia, in August 2020.* The 20 full papers and 16 short papers presented together with 18 posters were carefully reviewed and selected from 82 submissions. The papers are organized in the following topical sections: diagrams in mathematics; diagram design, principles, and classification; reasoning with diagrams; Euler and Venn diagrams; empirical studies and cognition; logic and diagrams; and posters. *The conference was held virtually due to the COVID-19 pandemic. The chapters ‘Modality and Uncertainty in Data Visualization: A Corpus Approach to the Use of Connecting Lines,’ ‘On Effects of Changing Multi-Attribute Table Design on Decision Making: An Eye Tracking Study,’ ‘Truth Graph: A Novel Method for Minimizing Boolean Algebra Expressions by Using Graphs,’ ‘The DNA Framework of Visualization’ and ‘Visualizing Curricula’ are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Graphical Models, Exponential Families, and Variational Inference

Graphical Models, Exponential Families, and Variational Inference

Author: Martin J. Wainwright

Publisher: Now Publishers Inc

Published: 2008

Total Pages: 324

ISBN-13: 1601981848

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The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate statistical models in the exponential family.


Book Synopsis Graphical Models, Exponential Families, and Variational Inference by : Martin J. Wainwright

Download or read book Graphical Models, Exponential Families, and Variational Inference written by Martin J. Wainwright and published by Now Publishers Inc. This book was released on 2008 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate statistical models in the exponential family.

Diagrammatic Representation and Inference

Diagrammatic Representation and Inference

Author: Tim Dwyer

Publisher: Springer

Published: 2014-07-23

Total Pages: 311

ISBN-13: 3662440431

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This book constitutes the refereed proceedings of the 8th International Conference on the Theory and Application of Diagrams, Diagrams 2014, held in Melbourne, VIC, Australia in July/August 2014. The 15 revised full papers and 9 short papers presented together with 6 posters were carefully reviewed and selected from 40 submissions. The papers have been organized in the following topical sections: diagram layout, diagram notations, diagramming tools, diagrams in education, empirical studies and logic and diagrams.


Book Synopsis Diagrammatic Representation and Inference by : Tim Dwyer

Download or read book Diagrammatic Representation and Inference written by Tim Dwyer and published by Springer. This book was released on 2014-07-23 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on the Theory and Application of Diagrams, Diagrams 2014, held in Melbourne, VIC, Australia in July/August 2014. The 15 revised full papers and 9 short papers presented together with 6 posters were carefully reviewed and selected from 40 submissions. The papers have been organized in the following topical sections: diagram layout, diagram notations, diagramming tools, diagrams in education, empirical studies and logic and diagrams.

Elements of Causal Inference

Elements of Causal Inference

Author: Jonas Peters

Publisher: MIT Press

Published: 2017-11-29

Total Pages: 289

ISBN-13: 0262037319

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A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.


Book Synopsis Elements of Causal Inference by : Jonas Peters

Download or read book Elements of Causal Inference written by Jonas Peters and published by MIT Press. This book was released on 2017-11-29 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.